Recognition of stonefish from underwater video

There is thousands of organisms under the water and every group of organisms have many types or species. Some are dangerous and will attack when touched and some others will attack directly without any reason. In this research, a method that can recognize a stonefish, which is the most venomous fish in the world from a video to help divers or swimmers in open water to avoid danger, is presented. When a stonefish hides, it keeps its head visible until it can attack the small fish quickly. This property is used to formulate the algorithm. The video is enhanced using Gaussian filter, Median filter, and Wiener filter. The method uses a database of images that contain the images of the head of stonefish. The features of the stonefish head is detected from the video by comparing the features of head images in the database by using a part of the Speeded Up Robust Features (SURF) method. The features in the video are compared with the features of the images of the database by using the k-Nearest Neighbor algorithm and the Histogram. The results of the comparison will decide if there is a stonefish in the video or not. Finally, if there is a stonefish in the video, the system will generate a warning signal to help the divers or swimmers to move away from it immediately.